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The Rise of Whatever

(eev.ee)
628 points cratermoon | 1 comments | 04 Jul 25 04:48 UTC | HN request time: 0.001s | source
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tptacek ◴[04 Jul 25 05:29 UTC] No.44461381[source]▶
LLM output is crap. It’s just crap. It sucks, and is bad.

Still don't get it. LLM outputs are nondeterministic. LLMs invent APIs that don't exist. That's why you filter those outputs through agent constructions, which actually compile code. The nondeterminism of LLMs don't make your compiler nondeterministic.

All sorts of ways to knock LLM-generated code. Most I disagree with, all colorable. But this article is based on a model of LLM code generation from 6 months ago which is simply no longer true, and you can't gaslight your way back to Q1 2024.

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csomar ◴[04 Jul 25 05:59 UTC] No.44461544[source]▶
> LLM outputs are nondeterministic.

LLM outputs are deterministic. There is no intrinsic source of randomness. Users can add randomness (temperature) to the output and modify it.

> But this article is based on a model of LLM code generation from 6 months ago

There hasn't been much change in models from 6 months ago. What happened is that we have better tooling to sift through the randomly generated outputs.

I don't disagree with your message. You are being downvoted because a lot of software developers are butt-hurt by it. It is going to force a change in the labor market for developers. In the same way the author is butt-hurt that they didn't buy Bitcoin in the very early days (as they were aware of it) and missed the boat on that.

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reasonableklout ◴[04 Jul 25 06:41 UTC] No.44461746[source]▶
Nit: in practice, even at temperature 0, production LLM implementations have some non-determinism. One reason is because many floating point computations are technically non-commutative even when the mathematical operation is, and the order can vary if they are carried out in parallel by the GPU. For example, see: https://www.twosigma.com/articles/a-workaround-for-non-deter...
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1. jkhdigital ◴[04 Jul 25 07:16 UTC] No.44461959[source]▶
I ran into this a bit while working on my PhD research that used LLMs for steganography. The output had to be deterministic to reverse the encoding, and it was—as long as you used the same hardware. Encoding a message on a PC and then trying to decode on a phone broke everything.